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[JAX] Error checking for mesh resource and update GemmPrimitive to use global_mesh_resource().fsdp_resource (#2088)

* Enforce global MeshResource is set
Signed-off-by: Jeremy Berchtold <jberchtold@nvidia.com>

* Use global_mesh_resource().fsdp_resource in gemm primitive
Signed-off-by: Jeremy Berchtold <jberchtold@nvidia.com>

* Update tests
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* Update gemm.py
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* Update test_layer.py
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* fix fsdp
Signed-off-by: Phuong Nguyen <phuonguyen@nvidia.com>

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* Support setting collection name for quantizer set Flax variables in TransformerEngineBase flax module
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* Support creating quantizer set from a recipe directly
Signed-off-by: Jeremy Berchtold <jberchtold@nvidia.com>

* Fix debug error format string in gemm.py
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* Lint
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* enabled TE GEMM for all recipes
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* add warnings
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* fix lint
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* rm batch_dim, sequence_dim, sequence_parallel_output
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* rm lhs_quantized_colwise and rhs_quantized_colwise
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* rm unnecessary transpose_batch_sequence arg from some modules
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Revert "[JAX] Disable TE Norm Custom Calls (#1993)"

This reverts commit 6c970612

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Signed-off-by: Phuong Nguyen <phuonguyen@nvidia.com>

Disable Norm custom calls
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* new gemm operand specs processing
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* fix for lhs_non_specs
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[JAX] Fixing GemmPrimitive partitioning rules to handle tensor-parallelism correctly for sequence-parallel inputs (#1980)

* updated GemmPrimitive partitioning rules to explicitly control all-reduce vs. reduce-scatter for sequence-parallelism
Signed-off-by: Alp Dener <adener@nvidia.com>

* corrected handling of FSDP sharding for the RHS operand
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* use correct logical axes variable to identify sequence-parallel dim in LayerNormDenseGeneral
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* fixed linting issues
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* added assert on sequence-parallel options when GemmPrimitive is disabled
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* add manage_primitives() helper

* disable GEMM primitives for non-MXFP8 recipes

* implement the NVTE_JAX_CUSTOM_CALLS + deprecate NVTE_JAX_CUSTOM_CALLS_RE

* replace NVTE_JAX_CUSTOM_CALLS_RE with NVTE_JAX_CUSTOM_CALLS in TE tests and examples

* fix use_jax_gemm contextmanager
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* remove unnecessary padding
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* adapt the test_distributed_layernorm byte count
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* added XLA FFI custom op for TE/common nvte_cublas_gemm
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started GemmPrimitive, abstract done
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gemm custom op working with BF16, needs testing for FP8/MXFP8
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converted TE GEMM API to use ScaledTensor and added os ENV flag to use TE GEMM under general gemm() call
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BF16 tests passing, FP8 tests should be passing but contracting_dims has a scoping issue
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fp8 tests passing for E4M3, getting CUBLAS_STATUS_NOT_SUPPORTED for E5M2
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updated GEMM API to use separate LHS and RHS quantizers instead of a QuantizerSet
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new GemmPrimitive passing all Dense tests
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import cleanup and reverted code chunk movement
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removed unused .transpose() implementations from ScaledTensors
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all custom call tests passing on Hopper, GEMM-related tests cover both GemmPrimitive and native JAX impl
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removed direct calls to GemmPrimitive.enabled() from outside of cpp_extensions
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removed unused changes to ScaledTensor classes and debug prints
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* minor unit test cleanup
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* FP8 tests passing on Blackwell but MXFP8 outputs NaN
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* reverted dense and fuseddense changes, FP8 test passing on Hopper and Blackwell, MXFP8 has issues with E5M2
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* MXFP8 issue traced to scale factor padding with NaNs instead of zeros
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* padding scale with 2^-127 instead of nans
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* fix bug on rhs_scale_inv usage
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* cleanup E8M0 type converter use it in gemm.cpp
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* segfault fixed, passing all unittests on Blackwell
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* fix for fuseddense tests
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* fix workspace alignment
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* fixed GemmPrimitive custom partitioning to match jax.nn.scaled_matmul
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all unit tests passing on H100x8 node
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linting fixes
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fixed batch dimension numbers
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fixed FP8 scale sharding rule when there are no FP8 scales
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added error message for unsupported Shardy partitioner
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fixed test tolerances for FP8 cases
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fixed shardy test skip cases
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* moved reshape of encoder output in encoder examples to make custom partitioning rules work correctly
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* added helper functions for padding and unpadding block scales, changed GemmPrimitive to accept unpadded scales and pad them after sharding
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* updated shardy rules for all custom ops to decouple block scale rules from their tensors
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* fixed linting errors
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* changed unit test use_jax_gemm option to be a context to preserve external custom op settings, tightened multi-GPU encoder test tolerances, changed gemm() API to use contracting_dims and batched_dims separately instead of dimension_numbers
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* fixed typo in test utils
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* added sequence-first input warnings
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* fixed datasets version for JAX examples
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* reverting modification to force_1x_quantization decision
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* corrected gemm function syntax in unit tests
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* Fix JAX grouped gemm error on CUDA 12.9.1 & later by using 16B alignment for scale ptr
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* Pad MXFP8 scales with 2*-127 instead of NaNs
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* TensorUsage + FP8 GEMM with all layouts handling on BW
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* Support MXFP8 and handle empty matrices
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* Add support for Fused Attn MLA head_dim_qk != head_dim_v
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	Modify FusedAttnHelper to accept different head_dims for qk and v and modify assert dims checks in parse_qkv_aval()
	Modify FusedAttnFwdPrimitive and FusedAttnBwdPrimitive to accept different head_dims for qk and v
	Modify Fused Attn related cpp and csrc extension API calls to accept different head_dims for qk and v
	Modify DotProductAttention call() to extract head dims separately for qk and v
	Modify the FusedAttn Tests to accommodate for API changes in FusedAttn API
	Add test case for head_dim_qk != head_dim_v (failing)
	Modify the baseline JAX appropriately to reshape the output vector based on v dims and not q dims
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* Fix context dims in general DPA in test_fused_attn
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* Fix dim for output tensor by replacing with v head dim rather than q head dim
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* Modify the fused attn jax unit test case for head dim qk != head dim v
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* Use new FusedAttnRunner function signature for separate hidden dim for qk and v in Fused Attn distributed tests
Code clean up
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* Fix usage of is_fused_attn signature in distributed tests
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* Remove unnecessary assert
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* add support for head dim > 128
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* remove debugging
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* raise tols slightly to tolerate 1/2048 mismatches
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* fix is_training for test_te_layer
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* add bprop support for blackwell
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* minor tweak for format
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* fix backend selection results
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* bump sm100 to sm100+
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* add sq=1 test for MLA
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* enable sq=1 for bprop
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* minor tweak in comments
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* fix head_dim logic and remove pytest skip
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* add FE fix for d>128
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* update FE again to take in small fixes
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* add cuDNN version info in L0 tests
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* increase tols for Unfused + large dim
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* Revert "add cuDNN version info in L0 tests"

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* fix tols for Unfused
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* fixes for jittable grouped_quantize

* fixes for jittable grouped_gemm

* fix contracting_dim for wgrad gemm

* exclude jitted grouped_gemm from the unit test as it does not work cudaGraph

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* Implemented GroupedDense and TestGroupedDense for BF16, FP16, and FP8 
* Fix GroupedGemmFFI cuBLAS workspace alignment bug
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Revert "[JAX] GroupedDense v.2 without dynamic shape (#1721)"

This reverts commit 5d01ef21

.
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* Implemented GroupedDense and TestGroupedDense for BF16, FP16, and FP8 
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* refactor the multi_stream utils + implement nvte_multi_tensor_quantize in TE/Common

* implement GroupedQuantizer and grouped_quantize in jaxx

* fix logical_axes_names for transpose tensor in ScaledTensor
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* fix otype for fp8 gemm
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* Fix 1x quantize kernel availability check on hopper

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* Use 1x quantization + jax transpose on BW for performance
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* Use 1x quantization on Hopper as well as it is also faster
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* Undo architecture check helper function
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* Lint
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* Support SWA in CP Ring Attn THD striped sharding
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* Add some comments; move check to _FusedAttnCPWithP2PHelper.check_supported()
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Remove unused check
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* removes unnecessary reshapes for FP8 GEMM

* use nn.jax.scaled_matmul
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* fp8 gemm with direct quant
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Update jax_scaled_masked_softmax to match TE kernel implementation
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Make primitive names more granular for better disabling granularity
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* removes unneccessary reshapes for FP8 GEMM

* use nn.jax.scaled_matmul
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* Enforce input sharding of norm primitive does not shard hidden dim
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* Fix partitioning issue in dact primitive causing NaN and add better shape checks before calling TE API
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* Move dact shape assertion from cpp to python
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* exclude GroupedGemm APIs
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Fix distributed layernorm test failure
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* Update test_helper.py and add QuantizeConfig class for CurrentScaling
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* Format
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* Update multiprocessing current scaling tolerances
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* Uncomment test case that was disabled for testing
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* Remove commented out debug line
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* [JAX-Q] Single GPU current scaling for JAX
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* Fix scale check dtype for MXFP8 scales affecting tests using assert_bitwise_scaled_tensors
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* Address comments
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* Remove cast to fp32 for norm primitives now that zero-centered gamma dtype issue is fixed
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Check CuDNN version and apply unfused norm if
below a version with the fix
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* Correct the condition where padding_causal_mask was being mapped to scaled upper triangle
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* Fix Issue #1524
Signed-off-by: Kshitij Janardan Lakhani <klakhani@nvidia.com>

* Add a runner and test cases for jax.flax.module.Softmax class for fwd pass only
Segregate runner classes for Softmax module and softmax primitives
Signed-off-by: Kshitij Janardan Lakhani <klakhani@nvidia.com>

* Simplify logic when picking softmax primitives and softmax jax framework calls
Signed-off-by: Kshitij Janardan Lakhani <klakhani@nvidia.com>

* [pre-commit.ci] auto fixes from pre-commit.com hooks

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* Simplify the logic for performing jax based softmax
Signed-off-by: Kshitij Janardan Lakhani <klakhani@nvidia.com>

* Code clean up
Signed-off-by: Kshitij Janardan Lakhani <klakhani@nvidia.com>

* [pre-commit.ci] auto fixes from pre-commit.com hooks

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* Add support table for mask, SWA and Softmax type. Code linting
Signed-off-by: Kshitij Janardan Lakhani <klakhani@nvidia.com>

* [pre-commit.ci] auto fixes from pre-commit.com hooks

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* Explicit SWA conditons in comments. Fix Typo
Signed-off-by: Kshitij Janardan Lakhani <klakhani@nvidia.com>

* [pre-commit.ci] auto fixes from pre-commit.com hooks

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* Resolve typo to remove None in SWA comments section
Signed-off-by: Kshitij Janardan Lakhani <klakhani@nvidia.com>

* [pre-commit.ci] auto fixes from pre-commit.com hooks

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Signed-off-by: Kshitij Janardan Lakhani <klakhani@nvidia.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>